Luminance-Based Video Coding for HDR Artifact Reduction
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Solution Overview
Problem
Traditional video coding standards, such as HEVC, struggle to maintain visual quality when encoding and decoding high dynamic range (HDR) images due to limited bit depths and lossy compression, resulting in noticeable visual artifacts, especially in bright and dark areas.
Innovation Solution
The implementation of luminance-dependent signal processing operations in video encoders and decoders, which adapt characteristics like bit depth, filtering, and quantization based on luminance levels, to minimize errors and improve compression efficiency across different regions of an image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional video coding standards (HEVC, H.264/AVC) are used to encode HDR images, then compression efficiency is achieved, but visual quality deteriorates with noticeable artifacts in bright and dark areas
Solution Approach 1:
The patent applies different signal processing operations to different luminance regions within the image. Specifically, it performs luminance-dependent signal processing where bright areas, midtone areas, and dark areas are processed differently to preserve visual quality in each region while maintaining compression efficiency.
Solution Approach 2:
The patent changes processing parameters based on luminance levels. It determines whether to perform signal processing operations based on luminance characteristics of image regions, and adjusts quantization parameters, filtering operations, and transformation methods according to the luminance range of different areas.
2Quantity of substance
If post-production images are compressed to reduce data amount for transmission and storage, then data volume is reduced, but coding errors increase causing visual artifacts
Solution Approach 1:
The patent applies different compression and signal processing operations to different luminance regions. Bright areas, midtone areas, and dark areas undergo different processing to minimize coding errors in each region while achieving overall data reduction.
Solution Approach 2:
The patent performs luminance analysis and determines processing strategies before actual compression. It identifies luminance ranges and selects appropriate signal processing operations in advance to prevent coding errors rather than correcting them after compression.
3Device complexity
If uniform signal processing is applied across all luminance levels, then device complexity is reduced, but visual quality deteriorates in specific regions like highlights and shadows
Solution Approach 1:
The patent divides the image into different luminance regions (bright, midtone, dark areas) and applies specific signal processing operations to each region. This localized approach improves visual quality in specific regions without requiring excessively complex uniform processing across the entire image.
Solution Approach 2:
The patent changes processing parameters based on luminance levels of different regions. It adjusts quantization parameters, filtering strength, and transformation methods according to whether the current processing region is bright, midtone, or dark, optimizing visual quality for each luminance range.
Data Source
AI summary
Sample data and metadata related to spatial regions in images may be received from a coded video signal. It is determined whether specific spatial regions in the images correspond to a specific region of luminance levels. In response to determining the specific spatial regions correspond to the specific region of luminance levels, signal processing and video compression operations are performed on sets of samples in the specific spatial regions. The signal processing and video compression operations are at least partially dependent on the specific region of luminance levels.